There is an ongoing need to improve the relevance of documents retrieved from document repositories in response to user queries. Knowledge workers and others who need to access and retrieve content are often frustrated when search results are not relevant to the task in hand and the time lost as a result impacts productivity. In addition, there is a need to enable individuals to receive recommendations of other individuals and/or documents to enable relevant people and documents to be found quickly and efficiently when faced with tasks.
Document retrieval, where document repositories comprise huge numbers of documents, is a non-trivial task since any solution must scale up in a robust and efficient manner so that practical, working solutions are enabled. Many existing solutions trade off relevance against the ability to scale, so that large scale systems often retrieve documents which are not as relevant. In the same way, recommendation systems can also suffer from this drawback.
The embodiments described below are not limited to implementations which solve any or all of the disadvantages of known document retrieval/identification systems.